Carga y limpieza preliminar de los datos
Los datos que se van a analizar en este documento proceden de la
compilaciĂ³n hecha por usuarios de Kaggle.
La fecha del anĂ¡lisis empieza el 22 de agosto de 2022, utilizando la
versiĂ³n 166 recopilada en la web anterior.
Cargar el dataset correctamente
Carga del dataset desde Python
import pandas as pd
datos = pd.read_csv("../data/covid_19_clean_complete.csv")
datos.head(10)
## Province/State ... WHO Region
## 0 NaN ... Eastern Mediterranean
## 1 NaN ... Europe
## 2 NaN ... Africa
## 3 NaN ... Europe
## 4 NaN ... Africa
## 5 NaN ... Americas
## 6 NaN ... Americas
## 7 NaN ... Europe
## 8 Australian Capital Territory ... Western Pacific
## 9 New South Wales ... Western Pacific
##
## [10 rows x 10 columns]
Carga del dataset con la librerĂa reticulate
pd <- import("pandas")
datos <- pd$read_csv("../data/covid_19_clean_complete.csv")
kable(head(datos, 10))
| NaN |
Afghanistan |
33.93911 |
67.70995 |
2020-01-22 |
0 |
0 |
0 |
0 |
Eastern Mediterranean |
| NaN |
Albania |
41.15330 |
20.16830 |
2020-01-22 |
0 |
0 |
0 |
0 |
Europe |
| NaN |
Algeria |
28.03390 |
1.65960 |
2020-01-22 |
0 |
0 |
0 |
0 |
Africa |
| NaN |
Andorra |
42.50630 |
1.52180 |
2020-01-22 |
0 |
0 |
0 |
0 |
Europe |
| NaN |
Angola |
-11.20270 |
17.87390 |
2020-01-22 |
0 |
0 |
0 |
0 |
Africa |
| NaN |
Antigua and Barbuda |
17.06080 |
-61.79640 |
2020-01-22 |
0 |
0 |
0 |
0 |
Americas |
| NaN |
Argentina |
-38.41610 |
-63.61670 |
2020-01-22 |
0 |
0 |
0 |
0 |
Americas |
| NaN |
Armenia |
40.06910 |
45.03820 |
2020-01-22 |
0 |
0 |
0 |
0 |
Europe |
| Australian Capital Territory |
Australia |
-35.47350 |
149.01240 |
2020-01-22 |
0 |
0 |
0 |
0 |
Western Pacific |
| New South Wales |
Australia |
-33.86880 |
151.20930 |
2020-01-22 |
0 |
0 |
0 |
0 |
Western Pacific |
Carga del dataset desde R
datos <- read.csv("../data/covid_19_clean_complete.csv", stringsAsFactors = T)
datos %>% head(10) %>% kable()
|
Afghanistan |
33.93911 |
67.70995 |
2020-01-22 |
0 |
0 |
0 |
0 |
Eastern Mediterranean |
|
Albania |
41.15330 |
20.16830 |
2020-01-22 |
0 |
0 |
0 |
0 |
Europe |
|
Algeria |
28.03390 |
1.65960 |
2020-01-22 |
0 |
0 |
0 |
0 |
Africa |
|
Andorra |
42.50630 |
1.52180 |
2020-01-22 |
0 |
0 |
0 |
0 |
Europe |
|
Angola |
-11.20270 |
17.87390 |
2020-01-22 |
0 |
0 |
0 |
0 |
Africa |
|
Antigua and Barbuda |
17.06080 |
-61.79640 |
2020-01-22 |
0 |
0 |
0 |
0 |
Americas |
|
Argentina |
-38.41610 |
-63.61670 |
2020-01-22 |
0 |
0 |
0 |
0 |
Americas |
|
Armenia |
40.06910 |
45.03820 |
2020-01-22 |
0 |
0 |
0 |
0 |
Europe |
| Australian Capital Territory |
Australia |
-35.47350 |
149.01240 |
2020-01-22 |
0 |
0 |
0 |
0 |
Western Pacific |
| New South Wales |
Australia |
-33.86880 |
151.20930 |
2020-01-22 |
0 |
0 |
0 |
0 |
Western Pacific |
Estructura de los datos y cambio nombre de las columnas
str(datos)
## 'data.frame': 49068 obs. of 10 variables:
## $ Province.State: Factor w/ 79 levels "","Alberta","Anguilla",..: 1 1 1 1 1 1 1 1 6 47 ...
## $ Country.Region: Factor w/ 187 levels "Afghanistan",..: 1 2 3 4 5 6 7 8 9 9 ...
## $ Lat : num 33.9 41.2 28 42.5 -11.2 ...
## $ Long : num 67.71 20.17 1.66 1.52 17.87 ...
## $ Date : Factor w/ 188 levels "2020-01-22","2020-01-23",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ Confirmed : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Deaths : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Recovered : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Active : int 0 0 0 0 0 0 0 0 0 0 ...
## $ WHO.Region : Factor w/ 6 levels "Africa","Americas",..: 3 4 1 4 1 2 2 4 6 6 ...
colnames(datos) = c("Provincia_Estado",
"Pais_Region",
"Latitud", # N+ o S-
"Longitud", # E+ o W-
"Fecha",
"Casos_Confirmados",
"Casos_Muertos",
"Casos_Recuperados",
"Casos_Activos",
"WHO_Region"
)
datos %>% head() %>% kable() # %>% kable_styling()
|
Afghanistan |
33.93911 |
67.70995 |
2020-01-22 |
0 |
0 |
0 |
0 |
Eastern Mediterranean |
|
Albania |
41.15330 |
20.16830 |
2020-01-22 |
0 |
0 |
0 |
0 |
Europe |
|
Algeria |
28.03390 |
1.65960 |
2020-01-22 |
0 |
0 |
0 |
0 |
Africa |
|
Andorra |
42.50630 |
1.52180 |
2020-01-22 |
0 |
0 |
0 |
0 |
Europe |
|
Angola |
-11.20270 |
17.87390 |
2020-01-22 |
0 |
0 |
0 |
0 |
Africa |
|
Antigua and Barbuda |
17.06080 |
-61.79640 |
2020-01-22 |
0 |
0 |
0 |
0 |
Americas |
Tipo de datos de cada columna
- Cualitativas se convierten
factor o bien
as.factor.
- Ordinales se convierten con
ordered.
- Cuantitativas se convierten con
as.numeric.
El tipo de dato fecha y su manipulaciĂ³n
Cambiar la columna fecha a tipo Date:
#datos$Fecha %<>% as.Date(format="%Y-%m-%d")
datos$Fecha %<>% ymd() # Con librerĂa lubridate
str(datos)
## 'data.frame': 49068 obs. of 10 variables:
## $ Provincia_Estado : Factor w/ 79 levels "","Alberta","Anguilla",..: 1 1 1 1 1 1 1 1 6 47 ...
## $ Pais_Region : Factor w/ 187 levels "Afghanistan",..: 1 2 3 4 5 6 7 8 9 9 ...
## $ Latitud : num 33.9 41.2 28 42.5 -11.2 ...
## $ Longitud : num 67.71 20.17 1.66 1.52 17.87 ...
## $ Fecha : Date, format: "2020-01-22" "2020-01-22" ...
## $ Casos_Confirmados: int 0 0 0 0 0 0 0 0 0 0 ...
## $ Casos_Muertos : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Casos_Recuperados: int 0 0 0 0 0 0 0 0 0 0 ...
## $ Casos_Activos : int 0 0 0 0 0 0 0 0 0 0 ...
## $ WHO_Region : Factor w/ 6 levels "Africa","Americas",..: 3 4 1 4 1 2 2 4 6 6 ...
\[Casos\ Confirmados = Muertos +
Recuperados + Enfermos\]
# Lo siguiente da lo mismo que la columna Casos_Activos, pero en el dataset que se
# utilizĂ³ en el curso no aparecĂa
datos %<>% # Ventaja que nos ofrece la librerĂa magrittr
mutate(Casos_Enfermos = Casos_Confirmados - Casos_Muertos - Casos_Recuperados)
datos %>%
filter(Casos_Confirmados > 10000) %>%
head() %>%
kable()
| Hubei |
China |
30.9756 |
112.2707 |
2020-02-02 |
11177 |
350 |
295 |
10532 |
Western Pacific |
10532 |
| Hubei |
China |
30.9756 |
112.2707 |
2020-02-03 |
13522 |
414 |
386 |
12722 |
Western Pacific |
12722 |
| Hubei |
China |
30.9756 |
112.2707 |
2020-02-04 |
16678 |
479 |
522 |
15677 |
Western Pacific |
15677 |
| Hubei |
China |
30.9756 |
112.2707 |
2020-02-05 |
19665 |
549 |
633 |
18483 |
Western Pacific |
18483 |
| Hubei |
China |
30.9756 |
112.2707 |
2020-02-06 |
22112 |
618 |
817 |
20677 |
Western Pacific |
20677 |
| Hubei |
China |
30.9756 |
112.2707 |
2020-02-07 |
24953 |
699 |
1115 |
23139 |
Western Pacific |
23139 |
datos %>%
filter(Casos_Enfermos < 0) %>%
arrange(Provincia_Estado, Fecha) %>%
kable()
|
Liechtenstein |
47.140000 |
9.55000 |
2020-06-23 |
82 |
2 |
81 |
-1 |
Europe |
-1 |
|
Uganda |
1.373333 |
32.29028 |
2020-07-20 |
1069 |
0 |
1071 |
-2 |
Africa |
-2 |
| Channel Islands |
United Kingdom |
49.372300 |
-2.36440 |
2020-05-23 |
558 |
45 |
515 |
-2 |
Europe |
-2 |
| Channel Islands |
United Kingdom |
49.372300 |
-2.36440 |
2020-05-24 |
558 |
45 |
517 |
-4 |
Europe |
-4 |
| Channel Islands |
United Kingdom |
49.372300 |
-2.36440 |
2020-05-25 |
559 |
45 |
517 |
-3 |
Europe |
-3 |
| Channel Islands |
United Kingdom |
49.372300 |
-2.36440 |
2020-05-30 |
560 |
45 |
525 |
-10 |
Europe |
-10 |
| Channel Islands |
United Kingdom |
49.372300 |
-2.36440 |
2020-05-31 |
560 |
45 |
528 |
-13 |
Europe |
-13 |
| Channel Islands |
United Kingdom |
49.372300 |
-2.36440 |
2020-06-01 |
560 |
45 |
528 |
-13 |
Europe |
-13 |
| Channel Islands |
United Kingdom |
49.372300 |
-2.36440 |
2020-06-02 |
560 |
46 |
528 |
-14 |
Europe |
-14 |
| Hainan |
China |
19.195900 |
109.74530 |
2020-03-24 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.195900 |
109.74530 |
2020-03-25 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.195900 |
109.74530 |
2020-03-26 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.195900 |
109.74530 |
2020-03-27 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.195900 |
109.74530 |
2020-03-28 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.195900 |
109.74530 |
2020-03-29 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.195900 |
109.74530 |
2020-03-30 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.195900 |
109.74530 |
2020-03-31 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.195900 |
109.74530 |
2020-04-01 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
datos %>%
filter(Provincia_Estado == "Hainan") %>%
kable()
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-22 |
4 |
0 |
0 |
4 |
Western Pacific |
4 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-23 |
5 |
0 |
0 |
5 |
Western Pacific |
5 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-24 |
8 |
0 |
0 |
8 |
Western Pacific |
8 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-25 |
19 |
0 |
0 |
19 |
Western Pacific |
19 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-26 |
22 |
0 |
0 |
22 |
Western Pacific |
22 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-27 |
33 |
1 |
0 |
32 |
Western Pacific |
32 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-28 |
40 |
1 |
0 |
39 |
Western Pacific |
39 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-29 |
43 |
1 |
0 |
42 |
Western Pacific |
42 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-30 |
46 |
1 |
1 |
44 |
Western Pacific |
44 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-31 |
52 |
1 |
1 |
50 |
Western Pacific |
50 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-01 |
62 |
1 |
1 |
60 |
Western Pacific |
60 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-02 |
64 |
1 |
4 |
59 |
Western Pacific |
59 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-03 |
72 |
1 |
4 |
67 |
Western Pacific |
67 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-04 |
80 |
1 |
5 |
74 |
Western Pacific |
74 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-05 |
99 |
1 |
5 |
93 |
Western Pacific |
93 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-06 |
106 |
1 |
8 |
97 |
Western Pacific |
97 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-07 |
117 |
2 |
10 |
105 |
Western Pacific |
105 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-08 |
124 |
2 |
14 |
108 |
Western Pacific |
108 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-09 |
131 |
3 |
19 |
109 |
Western Pacific |
109 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-10 |
138 |
3 |
19 |
116 |
Western Pacific |
116 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-11 |
144 |
3 |
20 |
121 |
Western Pacific |
121 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-12 |
157 |
4 |
27 |
126 |
Western Pacific |
126 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-13 |
157 |
4 |
30 |
123 |
Western Pacific |
123 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-14 |
159 |
4 |
43 |
112 |
Western Pacific |
112 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-15 |
162 |
4 |
39 |
119 |
Western Pacific |
119 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-16 |
162 |
4 |
52 |
106 |
Western Pacific |
106 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-17 |
163 |
4 |
59 |
100 |
Western Pacific |
100 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-18 |
163 |
4 |
79 |
80 |
Western Pacific |
80 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-19 |
168 |
4 |
84 |
80 |
Western Pacific |
80 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-20 |
168 |
4 |
86 |
78 |
Western Pacific |
78 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-21 |
168 |
4 |
95 |
69 |
Western Pacific |
69 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-22 |
168 |
4 |
104 |
60 |
Western Pacific |
60 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-23 |
168 |
5 |
106 |
57 |
Western Pacific |
57 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-24 |
168 |
5 |
116 |
47 |
Western Pacific |
47 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-25 |
168 |
5 |
124 |
39 |
Western Pacific |
39 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-26 |
168 |
5 |
129 |
34 |
Western Pacific |
34 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-27 |
168 |
5 |
131 |
32 |
Western Pacific |
32 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-28 |
168 |
5 |
133 |
30 |
Western Pacific |
30 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-29 |
168 |
5 |
148 |
15 |
Western Pacific |
15 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-01 |
168 |
5 |
149 |
14 |
Western Pacific |
14 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-02 |
168 |
5 |
151 |
12 |
Western Pacific |
12 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-03 |
168 |
5 |
155 |
8 |
Western Pacific |
8 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-04 |
168 |
5 |
158 |
5 |
Western Pacific |
5 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-05 |
168 |
6 |
158 |
4 |
Western Pacific |
4 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-06 |
168 |
6 |
158 |
4 |
Western Pacific |
4 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-07 |
168 |
6 |
158 |
4 |
Western Pacific |
4 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-08 |
168 |
6 |
159 |
3 |
Western Pacific |
3 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-09 |
168 |
6 |
159 |
3 |
Western Pacific |
3 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-10 |
168 |
6 |
159 |
3 |
Western Pacific |
3 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-11 |
168 |
6 |
159 |
3 |
Western Pacific |
3 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-12 |
168 |
6 |
160 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-13 |
168 |
6 |
160 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-14 |
168 |
6 |
160 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-15 |
168 |
6 |
160 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-16 |
168 |
6 |
161 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-17 |
168 |
6 |
161 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-18 |
168 |
6 |
161 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-19 |
168 |
6 |
161 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-20 |
168 |
6 |
161 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-21 |
168 |
6 |
161 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-22 |
168 |
6 |
161 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-23 |
168 |
6 |
161 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-24 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-25 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-26 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-27 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-28 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-29 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-30 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-31 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-01 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-02 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-03 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-04 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-05 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-06 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-07 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-08 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-09 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-10 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-11 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-12 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-13 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-14 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-15 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-16 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-17 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-18 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-19 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-20 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-21 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-22 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-23 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-24 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-25 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-26 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-27 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-28 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-29 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-30 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-01 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-02 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-03 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-04 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-05 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-06 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-07 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-08 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-09 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-10 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-11 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-12 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-13 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-14 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-15 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-16 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-17 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-18 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-19 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-20 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-21 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-22 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-23 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-24 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-25 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-26 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-27 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-28 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-29 |
169 |
6 |
163 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-30 |
169 |
6 |
163 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-31 |
169 |
6 |
163 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-01 |
169 |
6 |
163 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-02 |
169 |
6 |
163 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-03 |
169 |
6 |
163 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-04 |
169 |
6 |
163 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-05 |
169 |
6 |
163 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-06 |
170 |
6 |
162 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-07 |
170 |
6 |
162 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-08 |
170 |
6 |
162 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-09 |
170 |
6 |
162 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-10 |
170 |
6 |
162 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-11 |
170 |
6 |
162 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-12 |
171 |
6 |
162 |
3 |
Western Pacific |
3 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-13 |
171 |
6 |
162 |
3 |
Western Pacific |
3 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-14 |
171 |
6 |
162 |
3 |
Western Pacific |
3 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-15 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-16 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-17 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-18 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-19 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-20 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-21 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-22 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-23 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-24 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-25 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-26 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-27 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-28 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-29 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-30 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-01 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-02 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-03 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-04 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-05 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-06 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-07 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-08 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-09 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-10 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-11 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-12 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-13 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-14 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-15 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-16 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-17 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-18 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-19 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-20 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-21 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-22 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-23 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-24 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-25 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-26 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-27 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
Datos anĂ³malos y sin sentido
# Corregir datos anĂ³malos y sin sentido
datos %>%
filter(Provincia_Estado == "Hainan", Casos_Enfermos < 0) %>%
mutate(Casos_Recuperados = Casos_Recuperados + Casos_Enfermos,
Casos_Enfermos = 0) %>%
kable()
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-24 |
168 |
6 |
162 |
-6 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-25 |
168 |
6 |
162 |
-6 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-26 |
168 |
6 |
162 |
-6 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-27 |
168 |
6 |
162 |
-6 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-28 |
168 |
6 |
162 |
-6 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-29 |
168 |
6 |
162 |
-6 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-30 |
168 |
6 |
162 |
-6 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-31 |
168 |
6 |
162 |
-6 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-01 |
168 |
6 |
162 |
-6 |
Western Pacific |
0 |
AnĂ¡lisis geogrĂ¡fico de los datos
#datos_europa = datos[datos$Latitud > 38 & datos$Longitud > -25 & datos$Longitud < 30 , ]
datos_europa = datos %>%
filter(Latitud > 38, between(Longitud, -25, 30))
nrow(datos_europa)
## [1] 8460
table(datos_europa$Pais_Region) %>%
as.data.frame() %>%
filter(Freq > 0) %>%
kable()
| Albania |
188 |
| Andorra |
188 |
| Austria |
188 |
| Belarus |
188 |
| Belgium |
188 |
| Bosnia and Herzegovina |
188 |
| Bulgaria |
188 |
| Croatia |
188 |
| Czechia |
188 |
| Denmark |
376 |
| Estonia |
188 |
| Finland |
188 |
| France |
188 |
| Germany |
188 |
| Greece |
188 |
| Holy See |
188 |
| Hungary |
188 |
| Iceland |
188 |
| Ireland |
188 |
| Italy |
188 |
| Kosovo |
188 |
| Latvia |
188 |
| Liechtenstein |
188 |
| Lithuania |
188 |
| Luxembourg |
188 |
| Moldova |
188 |
| Monaco |
188 |
| Montenegro |
188 |
| Netherlands |
188 |
| North Macedonia |
188 |
| Norway |
188 |
| Poland |
188 |
| Portugal |
188 |
| Romania |
188 |
| San Marino |
188 |
| Serbia |
188 |
| Slovakia |
188 |
| Slovenia |
188 |
| Spain |
188 |
| Sweden |
188 |
| Switzerland |
188 |
| United Kingdom |
564 |
datos_europa %>%
filter(Fecha == ymd("2020-03-15")) %>%
kable()
|
Albania |
41.15330 |
20.168300 |
2020-03-15 |
42 |
1 |
0 |
41 |
Europe |
41 |
|
Andorra |
42.50630 |
1.521800 |
2020-03-15 |
1 |
0 |
1 |
0 |
Europe |
0 |
|
Austria |
47.51620 |
14.550100 |
2020-03-15 |
860 |
1 |
6 |
853 |
Europe |
853 |
|
Belarus |
53.70980 |
27.953400 |
2020-03-15 |
27 |
0 |
3 |
24 |
Europe |
24 |
|
Belgium |
50.83330 |
4.469936 |
2020-03-15 |
886 |
4 |
1 |
881 |
Europe |
881 |
|
Bosnia and Herzegovina |
43.91590 |
17.679100 |
2020-03-15 |
24 |
0 |
0 |
24 |
Europe |
24 |
|
Bulgaria |
42.73390 |
25.485800 |
2020-03-15 |
51 |
2 |
0 |
49 |
Europe |
49 |
|
Croatia |
45.10000 |
15.200000 |
2020-03-15 |
49 |
0 |
1 |
48 |
Europe |
48 |
|
Czechia |
49.81750 |
15.473000 |
2020-03-15 |
253 |
0 |
0 |
253 |
Europe |
253 |
| Faroe Islands |
Denmark |
61.89260 |
-6.911800 |
2020-03-15 |
11 |
0 |
0 |
11 |
Europe |
11 |
|
Denmark |
56.26390 |
9.501800 |
2020-03-15 |
864 |
2 |
1 |
861 |
Europe |
861 |
|
Estonia |
58.59530 |
25.013600 |
2020-03-15 |
171 |
0 |
1 |
170 |
Europe |
170 |
|
Finland |
61.92411 |
25.748151 |
2020-03-15 |
244 |
0 |
10 |
234 |
Europe |
234 |
|
France |
46.22760 |
2.213700 |
2020-03-15 |
4499 |
91 |
12 |
4396 |
Europe |
4396 |
|
Germany |
51.16569 |
10.451526 |
2020-03-15 |
5795 |
11 |
46 |
5738 |
Europe |
5738 |
|
Greece |
39.07420 |
21.824300 |
2020-03-15 |
331 |
4 |
8 |
319 |
Europe |
319 |
|
Holy See |
41.90290 |
12.453400 |
2020-03-15 |
1 |
0 |
0 |
1 |
Europe |
1 |
|
Hungary |
47.16250 |
19.503300 |
2020-03-15 |
32 |
1 |
1 |
30 |
Europe |
30 |
|
Iceland |
64.96310 |
-19.020800 |
2020-03-15 |
171 |
5 |
8 |
158 |
Europe |
158 |
|
Ireland |
53.14240 |
-7.692100 |
2020-03-15 |
129 |
2 |
0 |
127 |
Europe |
127 |
|
Italy |
41.87194 |
12.567380 |
2020-03-15 |
24747 |
1809 |
2335 |
20603 |
Europe |
20603 |
|
Latvia |
56.87960 |
24.603200 |
2020-03-15 |
30 |
0 |
1 |
29 |
Europe |
29 |
|
Liechtenstein |
47.14000 |
9.550000 |
2020-03-15 |
4 |
0 |
1 |
3 |
Europe |
3 |
|
Lithuania |
55.16940 |
23.881300 |
2020-03-15 |
12 |
0 |
1 |
11 |
Europe |
11 |
|
Luxembourg |
49.81530 |
6.129600 |
2020-03-15 |
59 |
1 |
0 |
58 |
Europe |
58 |
|
Moldova |
47.41160 |
28.369900 |
2020-03-15 |
23 |
0 |
0 |
23 |
Europe |
23 |
|
Monaco |
43.73330 |
7.416700 |
2020-03-15 |
2 |
0 |
0 |
2 |
Europe |
2 |
|
Montenegro |
42.70868 |
19.374390 |
2020-03-15 |
0 |
0 |
0 |
0 |
Europe |
0 |
|
Netherlands |
52.13260 |
5.291300 |
2020-03-15 |
1135 |
20 |
0 |
1115 |
Europe |
1115 |
|
North Macedonia |
41.60860 |
21.745300 |
2020-03-15 |
14 |
0 |
1 |
13 |
Europe |
13 |
|
Norway |
60.47200 |
8.468900 |
2020-03-15 |
1221 |
3 |
1 |
1217 |
Europe |
1217 |
|
Poland |
51.91940 |
19.145100 |
2020-03-15 |
119 |
3 |
0 |
116 |
Europe |
116 |
|
Portugal |
39.39990 |
-8.224500 |
2020-03-15 |
245 |
0 |
2 |
243 |
Europe |
243 |
|
Romania |
45.94320 |
24.966800 |
2020-03-15 |
131 |
0 |
9 |
122 |
Europe |
122 |
|
San Marino |
43.94240 |
12.457800 |
2020-03-15 |
101 |
5 |
4 |
92 |
Europe |
92 |
|
Serbia |
44.01650 |
21.005900 |
2020-03-15 |
48 |
0 |
0 |
48 |
Europe |
48 |
|
Slovakia |
48.66900 |
19.699000 |
2020-03-15 |
54 |
0 |
0 |
54 |
Europe |
54 |
|
Slovenia |
46.15120 |
14.995500 |
2020-03-15 |
219 |
1 |
0 |
218 |
Europe |
218 |
|
Spain |
40.46367 |
-3.749220 |
2020-03-15 |
7798 |
289 |
517 |
6992 |
Europe |
6992 |
|
Sweden |
60.12816 |
18.643501 |
2020-03-15 |
1022 |
3 |
0 |
1019 |
Europe |
1019 |
|
Switzerland |
46.81820 |
8.227500 |
2020-03-15 |
2200 |
14 |
4 |
2182 |
Europe |
2182 |
| Channel Islands |
United Kingdom |
49.37230 |
-2.364400 |
2020-03-15 |
3 |
0 |
0 |
3 |
Europe |
3 |
| Isle of Man |
United Kingdom |
54.23610 |
-4.548100 |
2020-03-15 |
0 |
0 |
0 |
0 |
Europe |
0 |
|
United Kingdom |
55.37810 |
-3.436000 |
2020-03-15 |
3072 |
43 |
18 |
3011 |
Europe |
3011 |
|
Kosovo |
42.60264 |
20.902977 |
2020-03-15 |
0 |
0 |
0 |
0 |
Europe |
0 |
Ejercicio prĂ¡ctico: mi viaje a Potsman
Distancia euclĂdea:
\[d(x, y) = \sqrt{(x_{Lat} - y_{Lat})^2 +
(x_{Long} - y_{Long})^2}\]
distancia_grados <- function(x, y){
sqrt((x[1] - y[1])^2 + (x[2] - y[2])^2)
}
distancia_grados_potsdam <- function(x){
potsdam = c(52.366956, 13.906734)
distancia_grados(x, potsdam)
}
dist_potsdam <- apply(cbind(datos_europa$Latitud, datos_europa$Longitud),
MARGIN = 1,
FUN = distancia_grados_potsdam)
datos_europa %<>%
mutate(dist_potsdam = dist_potsdam)
datos_europa %>%
filter(between(Fecha, dmy("02-03-2020"), dmy("07-03-2020")),
dist_potsdam < 4) %>% # Radio menor de 4 grados
arrange(Pais_Region) %>% # Ordenar por paĂs
kable()
|
Czechia |
49.81750 |
15.47300 |
2020-03-02 |
3 |
0 |
0 |
3 |
Europe |
3 |
2.992142 |
|
Czechia |
49.81750 |
15.47300 |
2020-03-03 |
5 |
0 |
0 |
5 |
Europe |
5 |
2.992142 |
|
Czechia |
49.81750 |
15.47300 |
2020-03-04 |
8 |
0 |
0 |
8 |
Europe |
8 |
2.992142 |
|
Czechia |
49.81750 |
15.47300 |
2020-03-05 |
12 |
0 |
0 |
12 |
Europe |
12 |
2.992142 |
|
Czechia |
49.81750 |
15.47300 |
2020-03-06 |
18 |
0 |
0 |
18 |
Europe |
18 |
2.992142 |
|
Czechia |
49.81750 |
15.47300 |
2020-03-07 |
19 |
0 |
0 |
19 |
Europe |
19 |
2.992142 |
|
Germany |
51.16569 |
10.45153 |
2020-03-02 |
159 |
0 |
16 |
143 |
Europe |
143 |
3.658073 |
|
Germany |
51.16569 |
10.45153 |
2020-03-03 |
196 |
0 |
16 |
180 |
Europe |
180 |
3.658073 |
|
Germany |
51.16569 |
10.45153 |
2020-03-04 |
262 |
0 |
16 |
246 |
Europe |
246 |
3.658073 |
|
Germany |
51.16569 |
10.45153 |
2020-03-05 |
482 |
0 |
16 |
466 |
Europe |
466 |
3.658073 |
|
Germany |
51.16569 |
10.45153 |
2020-03-06 |
670 |
0 |
17 |
653 |
Europe |
653 |
3.658073 |
|
Germany |
51.16569 |
10.45153 |
2020-03-07 |
799 |
0 |
18 |
781 |
Europe |
781 |
3.658073 |
Mapas del mundo con rnaturalearth
# Antes se necesita instalar rnaturalearthdata
#install.packages("rnaturalearthdata")
world <- ne_countries(scale = "medium", returnclass = "sf")
datos$Pais_Region = factor(datos$Pais_Region, levels = c(levels(datos$Pais_Region), "United States"))
datos[datos$Pais_Region == "US", ]$Pais_Region = "United States"
world %>%
inner_join(datos, by = c("name" = "Pais_Region")) %>%
filter(Fecha == dmy("30-05-2020")) %>%
ggplot() +
geom_sf(color = "black", aes(fill = Casos_Confirmados)) +
#coord_sf(crs = "+proj=laea +lat_0=50 +lon_0=10 +units=m +ellps=GRS80") +
scale_fill_viridis_c(option = "plasma", trans = "sqrt") +
xlab("Longitud") + ylab("Latitud") +
ggtitle("Mapa del mundo", subtitle = "COVID-19") -> g
ggplotly(g) # para hacer el mapa interativo